A 3D Visualization and Management Framework for

A 3D Visualization and Management Framework for Geological Disaster Monitoring and Early Warning

based on Virtual Globes

Weifeng Ma

Faculty of Earth Sciences China University of Geosciences

Wuhan, China

maweifeng@https://www.360docs.net/doc/96111426.html,

Xiangdan Tang

Faculty of Earth Sciences China University of Geosciences

Wuhan, China tangxiangdan@https://www.360docs.net/doc/96111426.html,

Qianggen Yang

Network Center

China University of Geosciences

Wuhan, China

yangqg@https://www.360docs.net/doc/96111426.html,

Shengshan Hou

China Institute of Geoenvironment Monitoring

Beijing, China

houss@https://www.360docs.net/doc/96111426.html,

Abstract—The virtual globe-based 3D visualization is a unique opportunity to facilitate the user interface of geological disaster monitoring and early warning system by promoting intuitive 3D interaction and seamless integration of 3D visualization with spatially referenced and multi-scale data. This paper discusses the technical issues of developing a virtual globe-based 3D visualization and management framework for geological disaster monitoring and early warning, using Web Services and Service Oriented Architecture (SOA) to support multi-source and multi-scale data interoperability. With the service oriented architecture’s capability for integrating distributed resources, spatial information such as DEM, remote sensing image, geography, geology and others information is deployed as different services in one server or several geographically distributed servers on the Internet (Intranet). Geological disaster monitoring data, which is spatially referenced and multi-source data with additional temporal information, come from different databases, files or service such as Web Service, FTP, and Email and so on. A service based integration method is used to integrated multi-source monitoring data to a series of unified service that can be visualized in virtual globes. Other information such as text, graph, image and video also can be integrated into the system easily with this architecture. Geological disaster early warning tools based on monitoring data and spatial information are integrated and the results can be visualized in virtual globes, which can help day-to-day users and high-level decision makers perform professional analysis, understand the complex analytical results by a well-designed 3D visualization and interactive user interface. Auxiliary spatial analysis tools such as 3D distance measurement, slope calculation, filling and cutting analysis, terrain section analysis are also integrated to help end users perform geological disaster early warning.

Keywords-Virtual Globe; Geological Disaster; Visualization; Geological Disaster Early Warning; Three Gorges Area

I.I NTRODUCTION

Natural hazards like landslides, avalanches and debris flows can result in enormous property damage and human casualties in mountainous regions such as Three Gorges Area of china [1, 2]. As human activity increased, geological disasters becoming more serious, and the scope, size, number and distribution show a steady increase. Geological disasters have become a serious constraint factor in China's economic development. Geological disasters monitoring and early warning involves multi-source spatial and temporal data of remote sensing image, geography, land, geology, irrigation, meteorology, public security and medical data that stored in various research centers and government departments. In order to offer a solid technical infrastructure framework for geological disaster monitoring and early warning visualization and management, a web-based database and GIS structure must be developed. Most participants of geological disaster management are not IT and GIS professionals; therefore, A well-designed visualization and interactive user interface is very important in disaster monitoring and early warning processes too.

Virtual globes such as Google Earth, WorldWind, ArcGIS Explorer, and Skyline are more appealing, intuitive and easily understandable interfaces to geospatial data than traditional digital map, which all offer the visualization, management and analysis function for spatial data [3]. In order to offer a solid technical infrastructure for geological disaster monitoring and early warning visualization and management, a virtual globe-based visualization and management framework has been developed. The framework provide a unique opportunity to facilitate the user interface of geological disaster monitoring and early warning system that integrated distributed spatial information such as DEM, remote sensing image, geography, geology and others information with the service oriented

This research was supported by the National Natural Science Foundation of China (Grants 40901242), and third major scientific research projects of geological disasters prevention and control in Three Gorges Reservoir Area.

architecture’s capability. Geological disaster early warning results and monitoring data can be visualized on virtual globes also, which can help day-to-day users and high-level decision makers understand the complex data and analytical results.

This paper discusses the technical issues of developing the virtual globe-based 3D visualization and management framework for geological disaster monitoring and early warning.

II. T HE 3D VISUALIZATION AND MANAGEMENT FRAMEWORK BASED ON VIRTUAL GLOBES A. The Visualization and Management Framework Design The purpose of developing a visualization and management framework for geological disaster monitoring and early

warning were (1) to integrate the main data and information that participants of geological disaster management typically

use, (2) to integrate the different models and applications for

geological disaster monitoring and early warning. The data and

information includes management data, spatial data, and

monitoring data and so on.

The objectives for the framework were (1) to provide an

general schema for integrate, analysis and displaying

geographically referenced geological disaster information,

monitoring data and analysis results, (2) to process and analyze spatially distributed data, (3) to create various applications and tools that support geological disaster management and early

warning for day-to-day users and high-level decision makers.

Virtual Globe-based Client

Data Service

Database

Cache

DOM

DLG

Label DEM Adpater

Adpater

Adpater

WMS

WFS

WebGIS

Data

Interface

Data

Pre-Processing

System Spatial

Calculation Internet / Intranet

Spatial Analysis Early Warning Tools Monitoring Data

Management

… …… …

Sensor DB Sensor DB

Sensor data service

Sensor

Figure 1. The general schema of visualization and management framework

for geological disaster monitoring and early warning

The general framework schema design is shown in Fig.1. Four main parts can be distinguished: ? Virtual globe-based client layer. ?

Data service layer.

? Data integration layer. ?

Data layer.

Based on SOA, the architecture uses web service as its

basic element that provides all necessary spatial data, geological disaster management data and monitoring data for client layer. This architecture provides an extensible, loosely-coupled, dynamic resource sharing enabled and interoperable computing framework [4]. With the service oriented architecture’s capability for integrating distributed data and

information, spatial information such as DEM, remote sensing image, geography, geology and others information deployed as

different services in one server or several geographically

distributed servers on the Internet (Intranet) can be integrated easily. B. The Layers ? Data layer include distributed management and

attribution data, spatial data and monitoring data for

geological disaster monitoring and early warning. The

data can be stored in local relational database, spatial

database, files and remote or local services like WMS, WFS, WebGIS and other web services. The local spatial data can be imported to spatial database by data pre-processing system. The monitoring data from different sensors is stored in its own remote or local databases or files. ? Data integration layer provide unified data interface layer for model calculation, spatial analysis, spatial calculation and business logic based on a unified geological disaster and monitoring data model. The

layer can easily integrate existing spatial data by publishing this data as OGC service that can be integrate by adapter. The remote attribution data is integrated to data service layer by web service. By a service-oriented approach, the monitoring data that stored in its own database or file can also be integrated into unified database (Fig 1). ?

Data service layer provides all necessary management and attribution data, spatial data and monitoring data for virtual globe-based client layer. Data service layer also provides model calculation, spatial analysis, spatial calculation and business logic functions. A cache module is used to improve local and remote data fetch efficiency.

?

Virtual globe-based client layer is designed to visualize multi-source spatial and temporal data, geological disaster monitoring and early warning data and information for a 3D environment. A friendly and well-designed visualization and interactive user interface is designed based on virtual globes. Virtual globe-based client layer is composed of a series of applications and tools for geological disaster management and early warning.

C.Service-based Geological Disaster Monitoring Data

Integration

Geological disaster monitoring data, which is spatially referenced and multi-source data with additional temporal information, come from different distributed sensors and stored in local and remote databases, files or service such as Web Service, FTP, and Email and so on. By a service-oriented approach, every sensor data source need to implement a service based on a unified data model of geological disaster monitoring. For example:

? A sensor collect data and sent to an e-mail address via GPRS, so the service of this sensor should been a

program that can regularly receive e-mail from that

address, parse the e-mail content and write parser

results into the database.

? A sensor collect data and write data into its own database, so the service of this sensor should been a

program that can regularly read data from one database

and write data into other database.

?Some data from third party, such as weather forecast, should be downloaded from the remote server through

FTP service, parse download content and write parser

results into the database.

Then the different distributed monitoring data that stored in local or remote database, file can be integrate into unified database based on its own service that can read data from different monitoring data source (Fig 1).

D.Geological Disaster Early Warning

Early warning analysis model need read required input data and calculate required parameter, do early warning calculation, build early warning result, and display it on virtual globes. Early warning analysis model in [5, 6] is used in this paper. The Early warning analysis model use "sensitive factor" and "induced factor" as the input data to calculate the "risk factors" in geological disaster. A higher sensitivity factor and more intense geological disasters induced factor combined can cause a high level of risk factor of geological disasters, while a lower sensitivity factor of geological disasters or a weak induced factor can cause a lower level of risk factor of geological disasters.

Sensitive factor analysis is based on the geological disaster information and spatial data. First, single factor analysis is calculated based on the distribution of the geological disaster points and different spatial data that includes elevation, slope, slope type, stratigraphic and so on. Second, the weighted overlay analysis is made for single factor analysis results. Third, the spectrum analysis is made for overlay analysis results. And the last, according to the spectrum analysis results, the overlay analysis results were classified and sensitivity factor was calculated, which is the sensitivity distribution map (Fig 2).

The general procedure of the early warning analysis is shown in Fig.2. Sensitive factor analysis module of the system can re-calculate the sensitive factor automatically or manually while the spatial data such as geographic and geological changes or the geological disaster points data changes. Geological disaster induced factor map is calculated and interpolated by geological disaster monitoring data such as rainfall, weather forecast, displacement of fracture and so on. Here we use rainfall and weather forecast monitoring data to calculate the induced factor [5]. Then the early warning analysis is applied by the sensitive factor and induced factor using grid calculation [6].

Sensitivity Analysis

Geological

Disaster

Information

Management

Disaster

Infomation

Spatial Data

Factor

Analysis

Sensitivity

Factor

Monitoring

Data

Induced

Factor

Monitoring

Data

… …

Early

Warning

Analysis

Result

Factor

Analysis

…

3D

Visualization

Fig.3

Fig.5c, d

Figure 2. The flow chart of geological disaster early warning analysis Detailed calculation process of the early warning analysis is shown in Fig.3;

The early warning analysis visualization is shown in Fig.5c, d.

Virtual

Globes

Client

Early

Warning

Web Service

Input

Database

Client

Server

Web

Service

Proxy

Add GIS

Layer

Results

UI

1

2

3

8

Data

Process

Virtual Globes

Server Model

Caculation

4

5

6

Local Data

7

Figure 3. Detailed calculation process of the early warning analysis

Detailed calculation process of the early warning analysis is shown in Fig.3, which can be divided into eight steps: ?User select date and time for early warning analysis, user also can select appropriate sensitive factor to

replace the default;

?Based on user input, early warning analysis module call Web service to get geological disaster monitoring

data such as rainfall and weather forecast data for

analysis;

?Server-side Web services read data from monitoring database and return monitoring data upon request;

?

Based on the user input parameters and the monitoring data return from server, data pre-processing operation and interpolation are done. For example, interpolation of rainfall scatter data, generating raster map of rainfall factors;

? Model calculation;

? Generating raster map of results;

? The analysis results will be converted to data format for virtual globes client;

?

Visualization of the analysis results in Virtual Globes.

III. S AMPLE APPLICATIONS

The framework has been successfully applied to geological disaster monitoring and early warning system development of Three Gorges area and Ya'an city, Sichuan province, which was implemented on a virtual globes platform iTelluro, a

virtual globes platform developed by the Faculty of Earth Sciences, China University of Geosciences.

a

b

c

Figure 4. The virtual globe-based 3D visualization and interactive user

interface

a. Globe geologic map visualization based on virtual globes;

b. Terrain visualization based on DEM and remote sensing image data and 3D

distance measurement;

c. Interactive user interface based on virtual globes.

A well-designed visualization and interactive user interface is designed for disaster monitoring and early warning processes based on virtual globes (Fig 4). Spatial and temporal data of remote sensing image, geography, geology, monitoring data and other data that stored distributed can be integrated and visualized in one interface. Users can choose to display different thematic data on virtual globes, such as geological map (Fig 4a, Fig 5b), geographic map (Fig 4c, Fig 5a) and geological disaster early warning results data (Fig 5d).

Based on DEM data and remote sensing images, 3D terrain visualization can be restored for users (Fig 4b), and geographical, geological and other thematic maps can be overlapped on 3D terrain visualization, which can help users to understand the actual geographical and geological environment (Fig 4c, Fig 5a, Fig 5b).

Auxiliary spatial analysis tools such as 3D distance

measurement, slope calculation, filling and cutting analysis, terrain section analysis are also integrated to help end users

perform geological disaster early warning (Fig 4b).

a

b

c d

The framework provides a loosely coupled integration approach for different geological disasters model, tools and application integration. The geological disaster early warning tools based on monitoring data and spatial information are integrated to the framework. Fig 5c illustrate the user interface of the geological disaster early warning tools based on real-time monitoring data (including rainfall, displacement monitoring data and so on), weather forecast data, geological disaster information and other spatial information.

Geological disaster early warning results can be visualized in virtual globes. The different depths of blue color of the results represent different geological disaster warning level, which can help day-to-day users and high-level decision makers perform professional analysis, understand the complex analytical results by this well-designed 3D visualization and interactive user interface (Fig 5).

IV. C ONCLUSION AND FUTURE WORK

A virtual globe-based framework has been proposed in this paper to provide visualization and management for geological disaster monitoring and early warning. This virtual globe-based and Web Service Oriented Architecture (SOA) framework

facilitates a solid technical infrastructure for geological disaster monitoring and early warning visualization and management: ?With the virtual globes and service oriented architecture’s capability, spatial information such as

DEM, remote sensing image, geography, geology,

monitoring data and others information that deployed

as different services in one server or several

geographically distributed servers on the Internet

(Intranet) can be integrated into the framework easily.

?The framework provides a unique opportunity to facilitate the user interface of geological disaster

monitoring and early warning system with the virtual

globes and service oriented architecture’s capability.

?Based on DEM data and remote sensing images, 3D terrain visualization can be restored for users. Users

can choose to display different thematic data on virtual

globes, such as geological map, geographic map and

geological disaster early warning results data, and the

thematic maps can be overlapped on 3D terrain

visualization, which can help user to understand the

actual geographical and geological environment.

?The framework provides a loosely coupled integration approach for different geological disasters model, tools

and application integration. The geological disaster

early warning tools based on monitoring data and

spatial information and other applications or tools are

integrated to the framework easily.

?Auxiliary spatial analysis tools such as 3D distance measurement, slope calculation, filling and cutting

analysis, terrain section analysis are also integrated to

help end users perform geological disaster early

warning.

Our research work also raises some new issues. Each of the current generation of virtual globes uses its own schemes for tiling the curved surface of the Earth, and iTelluro do so. These systems are optimized for storage and display purposes, but have limitations for the analysis of global scale data and processes [7]. Our future work may consider how analysis can be done on the tiling data, and how to design an optimal structuring and indexing schemes that can support massive simulation of Earth surface processes and analysis.

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